Pervasive Monitoring of Offshore Aquaculture Installations using Moored Profilers

Lead Pi: Jeff Dusek · 02/2020 - 01/2022

Project number: R/RC-158

Co-PI: Alessandra Ferzoco, Olin College of Engineering

Co-PI: Joanna Carey, Babson College


Objectives: To develop a low-cost moored automatic mobile profiler with modular sensor payloads for pervasive monitoring of aquaculture farms throughout the full life-cycle of the installation, from site assessment to environmental impact analysis. To develop handling, launching, and storage techniques and devices for the profiler. To develop and implement hardware and software for position regulation by the profiler on existing cable types used in offshore aquaculture. To determine which environmental and biological sensors provide actionable data to offshore aquaculture stakeholders.

Methodology: Olin and Babson College undergraduate researchers working with guidance and support from college faculty and staff will develop a moored automatic mobile profiler and modular sensor payloads consistent with the monitoring needs of offshore aquaculture installations. The moored profiler will be designed to leverage existing offshore farm infrastructure by traveling on “cables of convenience” to gather environmental and physical measurements at depths relevant to farm operations. It will be tested in Massachusetts coastal waters in collaboration with industry and local farmers, and iterative design improvements will be made based on stakeholder feedback. A targeted business plan will also be developed.

Rationale: Moored automatic mobile profilers have proven a valuable tool for collecting oceanographic and biological measurements for features with vertical heterogeneity. The development of a platform and control techniques to enable depth-resolved profiling on existing farm cable infrastructure using commercially available sensors would bring high-resolution biophysical observations to the aquaculture industry without the need for costly and complex point-sensor networks.

Pervasive monitoring of water quality indicators in concert with observations of fish growth rate, feeding patterns, and behavior will allow biologists and farm managers to identify key operational welfare indicators and develop interventions to guard against catastrophic events.